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@@ -121,14 +121,14 @@ either HTTPS download or direct S3 access when running in the Amazon Web Service
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`us-west-2` region -- where data within NASA's Earthdata Cloud reside. `earthaccess` also supports
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streaming data directly into analysis-ready formats using `fsspec`[@fsspec] and
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constructing virtual Zarr stores from archival formats (e.g., HDF5 and NetCDF4) using
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DMR++ metadata [@dmrpp], powered by VirtualiZarr [@virtualizarr] and kerchunk [@kerchunk], enabling drastic improvements in access performance.
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DMR++ metadata [@dmrpp], powered by VirtualiZarr [@virtualizarr] and kerchunk [@kerchunk], enabling drastic improvements in access performance.
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# Statement of need
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NASA's Earth science data archive is one of the largest and most diverse collections of
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Earth observation data in the world, used by tens of thousands of researchers, educators,
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and decision-makers globally. However, the complexity of the underlying data infrastructure
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Earth observation data in the world, used by over ten million researchers, educators,
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and decision-makers globally[@nasa_esds_data_metrics]. However, the complexity of the underlying data infrastructure
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presents a significant barrier to scientific productivity. A typical data access workflow
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requires a researcher to: (1) authenticate with NASA Earthdata Login; (2) discover
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relevant datasets and granules through the CMR API; (3) parse metadata to obtain download
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must now contend with two possible access paradigms, traditional HTTPS downloads and S3-based
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access. These both may even occur within a single analysis workflow. During workshops organized by NASA
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Openscapes [@nasa_openscapes; @lowndes2019], the need for simpler tools became evident.
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`earthaccess` was created to address this gap: it provides uniform access to NASA
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Earthdata regardless of data storage location and handles authentication, credentials, and tokening behind the scenes, enabling researchers to focus more on scientific interpretation and discovery.
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`earthaccess` was created to address this gap: it provides uniform access to NASA
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Earthdata regardless of data storage location and handles authentication, credentials, and tokening behind the scenes, enabling researchers to focus more on scientific interpretation and discovery.
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The target audience includes Earth scientists, remote sensing researchers, climate modelers,
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hydrologists, ecologists, and any researcher, application developer, or educator who needs
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to work with NASA Earth science data. The library is designed to be approachable for those new to Python -- with a
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